Publications de Aude Billard | EPFL Graph Search

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We introduce a unique intelligent system that relies on the centre of mass motions for conveying the user's motion intention. The objective of this device is to achieve a standing mobility vehicle for users with lower body impairments, such as spinal cord injury (SCI) while allowing the usage of their remaining motion capabilities in the upper body for achieving standing and sitting transitions without the need for external power. The device relies on a smart mechanism that combines passive actuators (gas-s

The problem of acquiring multiple tasks from demonstration is typi- cally divided in two sequential processes: (1) the segmentation or identification of different subgoals/subtasks and (2) a separate learning process that parameterizes a control policy for ...

We present a control framework for achieving a robust object grasp and manipulation in hand. In-hand manipulation remains a demanding task as the object is never stable and task success relies on carefully synchronizing the fingers' dynamics. Indeed, finge ...

Robotic assistance via motorized robotic arm manipulators can be of valuable assistance to individuals with upper-limb motor disabilities. Brain-computer interfaces (BCI) offer an intuitive means to control such assistive robotic manipulators. However, BCI ...

The importance of construction automation has grown worldwide, aiming to deliver new machineries for the automation of roads, tunnels, bridges, buildings and earth-work construction. This need is mainly driven by (i) the shortage and rising costs of skille ...

Robot PbD started about 30 years ago, growing importantly during the past decade. The rationale for moving from purely preprogrammed robots to very flexible user-based interfaces for training the robot to perform a task is three-fold. First and foremost, PbD, also referred to as {\em imitation learning} is a powerful mechanism for reducing the complexity of search spaces for learning. When observing either good or bad examples, one can reduce the search for a possible solution, by either starting the search

We model the dynamics of non-linear discrete (i.e. point-to- point) robot motions as a time-independent system described by an autonomous dynamical system (DS). We propose an iterative algorithm to estimate the form of the DS through a mixture of Gaussian ...

Praxic functions are frequently altered following brain lesion, giving rise to apraxia - a complex pattern of impairments that is difficult to assess or interpret. In this chapter, we review the current taxonomies of apraxia and related cognitive and neuro ...

This abstract addresses the question of human imitation through convergent evidence from neuroscience, using tools from machine learning. In particular, we consider a deficit in imitation of meaningless gestures (i.e., hand postures relative to the head) following callosal brain lesion (i.e., disconnected hemispheres). We base our work on the rational that looking at how imitation in apraxic patients is impaired can unveil its underlying neural principles. We ground the functional architecture and informati

Myoelectric prostheses allow users to recover lost functionality by controlling a robotic device with their remaining muscle activity. Such commercial devices can give users a high level of autonomy, but still do not approach the dexterity of the intact hu ...

The human hand is often viewed as the pinnacle of dexterity. Yet, its asymmetric shape and unique thumb largely limit its dexterity. Artificial and robotic hands have often departed from anthropomorphic design. With two or three fingers distributed in a uniform manner, traditional industrial robotic hands aimed at preserving symmetry, and facilitating manipulation. They remain, however, extremely far from human dexterity, capable solely of picking and placing tasks, one object at a time. We present a revers

Two years ago, I was writing the first of these columns as I launched into my two-year presidency. As I write this column, I am still three months away from the end, but I feel encompassed to step back and review this two-year ride, which felt more like a rocket flight than a stroll in nature. Throughout these two years, my actions as the IEEE Robotics and Automation Society (RAS) president have been led by two primary goals, 1) guaranteeing the quality of the science we publish and promote, which is a cha

In this chapter, we explore the issue of encoding, recognizing, generalizing and reproducing arbitrary gestures. We address one major and generic issue, namely how to discover the essence of a gesture, i.e. how to find a representation of the data that encapsulates only the key aspects of the gesture, and discards the intrinsic variability across people motions. The model is tested and validated in a humanoid robot, using kinematics data of human motion. In order for the robot to learn new skills by imitati

This paper contributes a novel framework that enables a robotic agent to efficiently learn and synthesize believable handwriting motion. We situate the framework as a foundation with the goal of allowing children to observe, correct and engage with the rob ...

Many manipulations in human everyday activities rely on the collaboration of our two hands. Bimanual fine manipulation tasks are particularly demanding as precise coordination among fingers of both hands is required. Yet, despite the abundant degrees of freedom (DoFs) need to be controlled, humans can perform such tasks nearly effortlessly. Ample evidence suggests that the human central nervous system (CNS) predetermines hand poses that are compatible with task conditions (e.g. task objective, physical prop

Dynamic manipulation, such as robot tossing or throwing objects, has recently gained attention as a novel paradigm to speed up logistic operations. However, the focus has predominantly been on the object's landing location, irrespective of its final orientation. In this work, we present a method enabling a robot to accurately "throw-flip" objects to a desired landing pose (position and orientation). Conventionally, objects thrown by revolute robots suffer from parasitic rotation, resulting in highly restric

We present a probabilistic architecture for solving generically the problem of extracting the task constraints through a Programming by Demonstration (PbD) framework and for generalizing the acquired knowledge to various situations. In previous work, we pr ...

We aim at merging technologies from information technology, roomware, and robotics in order to design adaptive and intelligent furniture. This paper presents design principles for our modular robots, called Roombots, as future building blocks for furniture ...

Autonomous navigation in highly populated areas remains a challenging task for robots because of the difficulty in guaranteeing safe interactions with pedestrians in unstructured situations. In this work, we present a crowd navigation control framework tha ...

The human hand is a versatile and complex system with dexterous manipulation capabilities. For the transfer of human grasping capabilities to humanoid robotic and prosthetic hands, an understanding of the dynamic characteristics of grasp motions is fundame ...

Aude Billard

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Materializing Personal Standing Mobility from Design to Shared Control

Learning Stable Task Sequences from Demonstration with Linear Parameter Varying Systems and Hidden Markov Models

Adaptive Fingers Coordination for Robust Grasp and In-Hand Manipulation Under Disturbances and Unknown Dynamics

Customizing skills for assistive robotic manipulators, an inverse reinforcement learning approach with error-related potentials

RoBétArmé Project: Human-robot collaborative construction system for shotcrete digitization and automation through advanced perception, cognition, mobility and additive manufacturing skills

Survey: Robot Programming by Demonstration

BM: An Iterative Method to Learn Stable Non-Linear Dynamical Systems with Gaussian Mixture Models

Apraxia: a review

A Neurocomputational Model of Impaired Imitation

Shared human–robot proportional control of a dexterous myoelectric prosthesis

A Robotic Hand Surpassing Human Capabilities in Dexterity and Functionality

A Two-Year Review of My Work as IEEE RAS President [President's Message]

Learning of Gestures by Imitation in a Humanoid Robot

Synthesizing Robotic Handwriting Motion by Learning from Human Demonstrations

Effect of task conditions on human hand pose selection strategies in bimanual fine manipulation tasks

Learning to Throw-Flip

Statistical Learning by Imitation of Competing Constraints in Joint Space and Task Space

Roombots-Mechanical Design of Self-Reconfiguring Modular Robots for Adaptive Furniture

Pedestrian-Robot Interactions on Autonomous Crowd Navigation: Reactive Control Methods and Evaluation Metrics

On Force Synergies in Human Grasping Behavior